The Way Cloud-based Machine Learning Can Help Automotive Businesses Succeed

October 29, 2018 / GuidesFor Team

Automotive businesses deal with cars, their parts, their maintenance, and improvement. It is a little impossible to consider the automotive industry getting tangled with cloud and computer technology. Well, the biggest surprise is that this industry could rely heavily on the data stored on cloud systems. As a matter of fact, Rapid Scale noted that this is the top industry to benefit from the cloud.

Through cloud-based machine learning, customers will be fulfilled by efficient service by keeping track of inventories, getting help, and use other data. Before anyone would know, cloud-based machine learning will actually lessen irate clients ringing the customer service hotline while workers will be able to move smoothly as information is readily available for them. – Crischellyn Abayon

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The cloud services market is growing rapidly, presenting a large revenue opportunity for cloud service providers. To compete in this fast-paced market, you need an infrastructure that lets you securely deliver services to multiple tenants, streamline operations, track usage and chargeback, and adapt quickly to technology changes. Scalability, flexibility, and efficiency are essential to differentiating your business.

We have distilled public cloud adoption considerations into a short list, selecting considerations relevant to choosing a public cloud environment for Infrastructure-as-a-Service. As many of these considerations also apply in various degrees to other types of services, as well as to hybrid IT infrastructures more broadly, also consider your own detailed IT governance plans and best practices—as well as the external risk assessment and security controls documents of your choice.

Usually characterized as conservative and resistant to change, the financial services industry has been challenged by financial technology (fintech) companies that compete by combining digital transformation, social media, and big data analytics to replace traditional models with innovative, data-led approaches and modernized IT infrastructures.